Basic Statistics for Behavioral Sciences - Chapter 5

These flashcards cover key vocabulary and concepts related to measures of variability in statistics, as outlined in Chapter 5 of Basic Statistics for Behavioral Sciences.

Measures of Variability

Describes the extent to which scores in a distribution differ from each other.

Range

The distance between the highest and lowest scores in a distribution.

Variance

A measure of variability that indicates how much scores are spread out around the mean.

Standard Deviation

The square root of the variance, representing the average distance of scores from the mean.

Deviation

The difference between a score and the mean, indicating how far a score is from the average.

Degrees of Freedom

The number of values in a calculation that are free to vary; in estimating variance, it is usually N-1.

Population Variance

The actual variance of a population of scores.

Sample Variance

The average of the squared deviations around the mean, used as an estimate of population variance.

Normal Distribution

A symmetric distribution where most of the observations cluster around the central peak.

Proportion of Variance Accounted For

Indicates how much error in predictions is resolved when using relationships to predict scores.

Estimated Population Standard Deviation

An unbiased estimator of the population standard deviation, using N-1 in calculations.

Clump vs. Spread

Concept in statistics referring to measures of central tendency (clump) and measures of variability (spread).

Computational Formula

A faster method to calculate sample variance and standard deviation as opposed to using definitional formulas.

Mean

The average score of a distribution, serving as a reference point in calculating variance and standard deviation.